Targeted proteomics of solid cancers: from quantification of known biomarkers towards reading the digital proteome maps
Language English Country Great Britain, England Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't, Review
- Keywords
- biomarker, bodily fluids, cancer, data independent acquisition, selected reaction monitoring, tissue, verification,
- MeSH
- Early Detection of Cancer methods MeSH
- Mass Spectrometry methods MeSH
- Humans MeSH
- Biomarkers, Tumor chemistry metabolism MeSH
- Proteome chemistry metabolism MeSH
- Proteomics methods MeSH
- Animals MeSH
- Check Tag
- Humans MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
- Names of Substances
- Biomarkers, Tumor MeSH
- Proteome MeSH
The concept of personalized medicine includes novel protein biomarkers that are expected to improve the early detection, diagnosis and therapy monitoring of malignant diseases. Tissues, biofluids, cell lines and xenograft models are the common sources of biomarker candidates that require verification of clinical value in independent patient cohorts. Targeted proteomics - based on selected reaction monitoring, or data extraction from data-independent acquisition based digital maps - now represents a promising mass spectrometry alternative to immunochemical methods. To date, it has been successfully used in a high number of studies answering clinical questions on solid malignancies: breast, colorectal, prostate, ovarian, endometrial, pancreatic, hepatocellular, lung, bladder and others. It plays an important role in functional proteomic experiments that include studying the role of post-translational modifications in cancer progression. This review summarizes verified biomarker candidates successfully quantified by targeted proteomics in this field and directs the readers who plan to design their own hypothesis-driven experiments to appropriate sources of methods and knowledge.
References provided by Crossref.org
Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry